• The quantilogram : With an app...

Treffer: The quantilogram : With an application to evaluating directional predictability

Title:
The quantilogram : With an application to evaluating directional predictability
Authors:
LINTON, O, WHANG, Yoon-Jae
Source:
Semiparametric methods in econometricsJournal of econometrics. 141(1):250-282
Publisher Information:
Amsterdam: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 1 p.1/4
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Inférence paramétrique, Parametric inference, Inférence non paramétrique, Nonparametric inference, Inférence à partir de processus stochastiques; analyse des séries temporelles, Inference from stochastic processes; time series analysis, Applications, Assurances, économie, finance, Insurance, economics, finance, Analyse donnée, Data analysis, Análisis datos, Analyse multivariable, Multivariate analysis, Análisis multivariable, Association statistique, Statistical association, Asociación estadística, Autocorrélation, Autocorrelation, Autocorrelación, Borne supérieure, Upper bound, Cota superior, Distribution statistique, Statistical distribution, Distribución estadística, Donnée économique, Economic data, Dato económico, Econométrie, Econometrics, Econometría, Estimation moyenne, Mean estimation, Estimación promedio, Estimation non paramétrique, Non parametric estimation, Estimación no paramétrica, Estimation statistique, Statistical estimation, Estimación estadística, Fonction répartition, Distribution function, Función distribución, Intervalle confiance, Confidence interval, Intervalo confianza, Médiane, Median, Mediana, Méthode statistique, Statistical method, Método estadístico, Processus stochastique, Stochastic process, Proceso estocástico, Prédictabilité, Predictability, Predictabilidad, Quantile, Cuantila, Série temporelle, Time series, Serie temporal, Test hypothèse, Hypothesis test, Test hipótesis, Test statistique, Statistical test, Test estadístico, Valeur critique, Critical value, Valor crítico, Variation journalière, Daily variation, Variación diaria, 60E05, 60E99, 62E10, 62F03, 62F25, 62G10, 62G15, 62H15, 62H20, 62M10, Estimation paramétrique, Rentabilité boursière, Stock return, C12; C13; C14; C22, Correlogram; Dependence; Efficient markets; Empirical process; Portmanteau; Quantiles
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Economics, London School of Economics, Houghton Street, London WC2A 2AE, United Kingdom
School of Economics, Seoul National University, Seoul 151-742, Korea, Republic of
ISSN:
0304-4076
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=19153142
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.19153142
Database:
PASCAL Archive

Weitere Informationen

We propose a new diagnostic tool for time series called the quantilogram. The tool can be used formally and we provide the inference tools to do this under general conditions, and it can also be used as a simple graphical device. We apply our method to measure directional predictability and to test the hypothesis that a given time series has no directional predictability. The test is based on comparing the correlogram of quantile hits to a pointwise confidence interval or on comparing the cumulated squared autocorrelations with the corresponding critical value. We provide the distribution theory needed to conduct inference, propose some model free upper bound critical values, and apply our methods to S&P500 stock index return data. The empirical results suggest some directional predictability in returns. The evidence is strongest in mid range quantiles like 5-10% and for daily data. The evidence for predictability at the median is of comparable strength to the evidence around the mean, and is strongest at the daily frequency.